ECWP Future Management Scenarios Landuse

This data is four future scenarios landuse for ECWP. It includes general landuse, impervious landuse as well as landuse classes. Last update date: June 28, 2021. Data source: ECWP landuse 2019, Draft Conceptual Peel SABE - December 2020, 2020.01.17_Mayfield ROPA Part C_Sub2 55. Scenario 1: Urban Expansion with Minimal Enhancements. Assumes urbanization of the remaining whitebelt* lands in the headwaters of the watershed. No enhancements to natural cover or stormwater management. Scenario 2: Urban Expansion with Mid-range Enhancements. Same as Scenario 1, with some enhancements to stormwater management, urban forest, and natural cover.
Includes the potential Greater Toronto Area (GTA) West Highway (i.e. 413).
Scenario 3: Urban Expansion with Optimal Enhancements. Same as Scenario 1, with a greater level of enhancements to stormwater management, urban forest, and natural cover than Scenario. Scenario 4: Existing Urban Boundary with Optimal Enhancements. Same as Scenario 3, except the current urban boundary is maintained in the headwaters.

Datasets available for download

Additional Info

Field Value
Last Updated May 19, 2026, 16:31 (UTC)
Created May 19, 2026, 16:31 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Title
Title for the Dataset.
ECWP Future Management Scenarios Landuse
Description
A description of the dataset.

This data is four future scenarios landuse for ECWP. It includes general landuse, impervious landuse as well as landuse classes. Last update date: June 28, 2021. Data source: ECWP landuse 2019, Draft Conceptual Peel SABE - December 2020, 2020.01.17_Mayfield ROPA Part C_Sub2 55. Scenario 1: Urban Expansion with Minimal Enhancements. Assumes urbanization of the remaining whitebelt* lands in the headwaters of the watershed. No enhancements to natural cover or stormwater management. Scenario 2: Urban Expansion with Mid-range Enhancements. Same as Scenario 1, with some enhancements to stormwater management, urban forest, and natural cover.
Includes the potential Greater Toronto Area (GTA) West Highway (i.e. 413).
Scenario 3: Urban Expansion with Optimal Enhancements. Same as Scenario 1, with a greater level of enhancements to stormwater management, urban forest, and natural cover than Scenario. Scenario 4: Existing Urban Boundary with Optimal Enhancements. Same as Scenario 3, except the current urban boundary is maintained in the headwaters.

Tags / Keywords
Keywords/tags categorizing the dataset.
Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
Dataset Size
Dataset size in megabytes.
68928.0
Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
Published Date
Published date of the dataset.
2022-09-22
Time Period Data Span (start date)
Start date of the data in the dataset.
Time Period Data Span (end date)
End date of time data in the dataset.
GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
Field Value
Access category
Type of access granted for the dataset (open, closed, service, etc).
public
License
License used to access the dataset.
Toronto and Region Conservation Authority (TRCA) Open Data Licence v1.0 - Toronto and Region Conservation Authority (TRCA)
Limits on use
Limits on use of data.
Location
Location of the dataset.
https://trca-camaps.opendata.arcgis.com/datasets/camaps::ecwp-future-management-scenarios-landuse
Data Service
Data service for accessing a dataset.
Owner
Owner of the dataset.
jason.tam
Contact Point
Who to contact regarding access?
Conservation Ontario
Contact Point Email
The email to contact regarding access?
[email protected]
Publisher
Publisher of the dataset.
Conservation Ontario
Publisher Email
Email of the publisher.
Author
Author of the dataset.
jason.tam
Author Email
Email of the author.
Accessed At
Date the data and metadata was accessed.
2023-07-04
Field Value
Identifier
Unique identifier for the dataset.
9b1a725139a14e379f60390a4e4cc888
Language
Language(s) of the dataset
English
Link to dataset description
A URL to an external document describing the dataset.
https://trca-camaps.opendata.arcgis.com/datasets/camaps::ecwp-future-management-scenarios-landuse
Persistent Identifier
Data is identified by a persistent identifier.
Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
Contains data about individuals
Does the data hold data about individuals?
Contains data about identifiable individuals
Does the data hold identifiable data about individual?
Contains Indigenous Data
Does the data hold data about Indigenous communities?
Portal Type
Platform type of the source portal.
Field Value
Version
Version of the datatset
None
Source
Source of the dataset.
None
Version notes
Version notes about the dataset.
Is version of another dataset
Link to dataset that it is a version of.
Other versions
Link to datasets that are versions of it.
Provenance Text
Provenance Text of the data.
Conservation Ontario
Provenance URL
Provenance URL of the data.
Temporal resolution
Describes how granular the date/time data in the dataset is.
GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
Field Value
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
Community Permission
Community permission (who gave permission).
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Number of data rows
If tabular dataset, total number of rows.
38205
Number of data columns
If tabular dataset, total number of unique columns.
41
Number of data cells
If tabular dataset, total number of cells with data.
1566405
Number of data relations
If RDF dataset, total number of triples.
Number of entities
If RDF dataset, total number of entities.
Number of data properties
If RDF dataset, total number of unique properties used by the triples.
Data quality
Describes the quality of the data in the dataset.
Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.

0 Comments

Please login or register to comment.